Home health care has been growing rapidly in past three decades because of the shift of health care delivery from hospitals to communities. There were approximately 12 million home care patients in 2010, and this number is expected to increase as the population ages. Healthcare associated infections (HAIs), a preventable adverse health outcome, are prevalent in home health care settings. An estimated 1.2 million infections occur annually among home care patients, and most are related to urinary catheter or intravenous (IV) catheters. Previous research studies on HAIs among home care patients were conducted at the local level, did not use current data, and were limited by small sample sizes and methodological flaws. Furthermore, no research has examined patients' living environments or caregivers characteristics. These elements are important in home care settings and are emphasized by the Association for Professionals in Infection Control and Epidemiology, Inc. for studies on home health care infection. Therefore, a study using a current national database with measurable environmental factors and caregiver characteristics, and utilizing sound methodology is imperative to better understand the epidemiology of HAIs in home care settings. The proposed study will address this challenge by using the Outcome and Assessment Information Set (OASIS) national home care dataset that measures patient socio-demographics, environmental factors, support systems, health status, functional status, and health service utilization characteristics. The Aims are to: 1) describe the incidence and trends of device-associated infections, specifically catheter associated urinary tract infections and intravenous catheter related infections, in home care settings; and 2) identify risk factors associated with these device-associated infections in home care settings. Data on home health care patients with indwelling urinary catheters or receiving home infusion therapy between 2000 and 2009 will be obtained from the OASIS dataset. Infection cases will be identified if patients were hospitalized or received emergency care for any of the two types of infection. The proportion of patients with infections will be calculated for each type of infection in each individual year. Ordinary least squares regressions will be used to determine the statistical significance of the trends. For Aim 2, only data from 2009 will be used. Multilevel Cox proportional hazard model will be used to identify the risk factors for each type of infection. The study findings will be a critical step in the development of a national surveillance system for home health care infections and provide a basis for future intervention programs to prevent and control infections in home health care settings.